Top 160 anomaly-detection open source projects

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

MemStream: Memory-Based Streaming Anomaly Detection

Mean-Shifted Contrastive Loss for Anomaly Detection

Official source code of "Fast Adaptive RNN Encoder-Decoder for Anomaly Detection in SMD Assembly Machine"

https://events.kaspersky.com/hackathon/

The Combined Anomalous Object Segmentation (CAOS) Benchmark

[ti]ny [li]ttle machine learning [tool]box - Machine learning, anomaly detection, one-class classification, and structured output prediction

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

Implementation of feature engineering from Feature engineering strategies for credit card fraud

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)

Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"

Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

A quick and dirty vehicle speed detector using video + anomaly detection

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.

基于智能计算框架nupic的异常检测restful Api.

Sherlock is an anomaly detection service built on top of Druid

Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Interactive Visualization to Build, Train and Test an Autoencoder with Tensorflow.js

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

anomaly detection by one-class SVM

Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo.

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Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

TOD: GPU-accelerated Outlier Detection via Tensor Operations

Code for reproducing f-AnoGAN in Pytorch

Feature Space Singularity for Out-of-Distribution Detection. (SafeAI 2021)

The Kubervisor allow you to control which pods should receive traffic or not based on anomaly detection.It is a new kind of health check system.

This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'

some anomaly detection models and experiments.

Main component extraction for outlier detection

Python toolbox for transfer learning.

A Ground Mobile Robot Perception Dataset, IEEE RA-L & IEEE T-CYB

A Python library for anomaly detection

The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks

A scikit-learn compatible library for anomaly detection